Remote detection of gaseous ammonia using the near infrared transmission properties of polyaniline

Ammonia is a key component of many industrial processes where it is used in very high concentrations. The applications range from high quality steel production and fertiliser manufacture, to the refrigeration of food products and ice ring leisure facilities. Ammonia escapes have been identified as a large and serious problem by both government and industry. Simple and robust ammonia sensors for remote monitoring applications remain an area of continuous interest.

Polyaniline is a conducting polymer used in ‘electronic nose’ instrumentation and has been shown to be electronically sensitive to ammonia. In this paper, we report on the application of electrochemically-prepared polyaniline films for the measurement of gaseous ammonia at 1300 nm. This wavelength corresponds to a region of high optical transmission for optical fibres and is also compatible with telecom devices and technology. A simple and robust measurement system based on a standard telecom 1300 nm LED is described and remote sensing using 100 m of duplex multimode fibre is demonstrated.

Typically, the transmission of the polyaniline films at 1300 nm increases by approximately 1% in response to gaseous ammonia levels of 6 ppm in 50% RH. This represents the lower limit of detection in our study. Although initially the sensors react to the presence of ammonia very fast it takes over several hours for the output to reach the equilibrium. Clearly this is impractical however, it is possible to differentiate between different concentrations of ammonia by taking two readings at fixed intervals. A calibration curve for the sensors was obtained using two readings 15 s apart. The response time of the polyanaline films was found to be insensitive to the humidity variations in the range of 30–70% RH, however, over the 10–90% variation the changes were of the same order of magnitude as those induced by 6 ppm of ammonia.     

基于近红外光谱的煤粉样品定量检测研究

针对煤质快速在线检测的需求,采用傅里叶变换近红外光谱结合不同的光谱预处理方法,即平滑处理方法、微分方法、多元散射校正方法、标准归一化处理方法分别建立了煤粉样品的水分、灰分和挥发分的偏最小二乘模型,并对模型的检测结果进行了十字交叉验证。结果表明,基于25点平滑处理方法建立的水分偏最小二乘模型较优,基于标准归一化处理方法建立的灰分偏最小二乘模型最佳,基于5点平滑处理方法建立的挥发分偏最小二乘模型精度最高,验证了应用傅里叶变换近红外光谱技术定量分析煤粉指标的可行性。     

基于多尺度形态学的红外图像边缘检测方法

提出了一种基于数学形态学算子的多尺度边缘检测方法。首先选取几个有代表性的结构元素对灰度图像进行边缘检测得到边缘图像。改变结构元素的尺寸大小可得到多尺度下的边缘图像,根据局部边缘生存期的长短将不同尺度下的边缘图像合成。对噪声大、边缘较模糊的红外图像进行了边缘检测与比较,实验表明该算法抗噪能力强,能得到更精细准确的边缘。     

应用多特征的红外弱小目标检测

红外弱小点目标的检测是红外搜索与跟踪的关键技术之一。融合小目标在空域和频域中的各种属性,将更有利于目标的检测。红外图像中主要分为背景、边缘以及目标三类信息,目标在空域中局部能量较大。将图像小波变换,获取图像的多方向性分解。研究发现目标在高频中具有方向不敏感性。为了更好地检测目标,计算各点的局部能量比以及方向离散值,将以上特征融合,得到图像的多特征统计值。采用Renyi信息熵分割达到检测目标的目的。利用序列图像中目标运动的连续性和轨迹的一致性以及目标的方差增长性,提出一种加权的方差增长方法过滤目标集,实现候选目标的准确定位。该算法有较好的自适应性,并且对背景变化敏感性较小。通过真实红外图像弱小目标的检测,检验了算法的有效性。     

基于ToF红外图像的手部轻量化检测算法设计与优化

嵌入式设备上实现快速精准的手部检测主要面临两个挑战：一是复杂的深度学习网络很难实现实时的手部检测;二是场景复杂性导致基于RGB彩色图像的手部检测算法准确率下降。与主流基于RGB图像的检测技术不同,基于ToF红外图像的轻量化手部检测算法实现了红外图像中手部的精准快速检测。首先,通过自主研发设备采集了22 419张静态红外图片,构建了用于手部检测的红外数据集;其次,通过对通用目标检测算法进行轻量化改进,设计了RetinaHand轻量化手部检测网络,其中采用了MobileNetV1和ShuffleNetV2两种不同的轻量化网络作为模型骨干网络,并提出了一种融合注意力机制的特征金字塔结构Attention-FPN;最后,在红外数据集上与常规方法进行了对比实验,验证了该方法的有效性。     

高精度可调式红外检测控制系统设计

检测系统是自动控制的核心，其精度及可靠性直接影响着控制过程的优劣。提出一种基于红外技术进行物体检测的设计方案。系统通过精度调节，可应用于机械、冶金、化工、纺织、食品等多领域的生产设备中，实现产品质量、安全保护等自动检测控制；阐述了系统工作原理及主要功能模块设计。     

壳聚糖固定化脲酶生物传感器选择性测定铜离子

基于重金属对脲酶的抑制作用,研制了用于测定铜离子的生物传感器。该生物传感器的制备以壳聚糖为载体,将脲酶固定于pH电极表面。由于壳聚糖对Cu2+的富集,该生物传感器展现出高灵敏度。在样品溶液中加入5 mmol/L NaI,可以消除Hg2+和Ag+的干扰,从而实现Cu2+的选择性检测。在0.005～0.5μg/mL的浓度范围内,脲酶活性的抑制率与Cu2+浓度的对数呈良好的线性响应关系,其检出限为0.002μg/mL。将使用后的生物传感器浸泡于0.5 mmol/L的EDTA溶液再生5 min,被Cu2+抑制的脲酶的活性可以得到恢复。     

基于红外成像多特征联合的乙烯气体泄漏检测

针对目前乙烯气体泄漏检测存在效率低、精度差以及无法准确标定泄漏位置等问题,提出了一种基于红外成像多特征联合的乙烯气体泄漏检测方法。该方法首先利用红外相机获取生产车间的红外视频图像,通过联合帧间差分和背景差分的方法获取疑似区域;其次对疑似区域进行泄漏气体成像的统计特征和小波能量变化特征分析,找出特征阈值;最后将多个特征阈值条件联合在一起,作出是否存在泄漏的判定。实验结果表明：该方法准确、高效且具备实时性,其泄漏检测的准确率达到95.6%。     

近红外光谱吸收法检测油气田中H2S体积分数

基于四川地区油气田高含硫现象,提出一种新型系统利用红外光谱吸收测量法检测H2S气体体积分数,有效解决传统气体检测技术中的杂质气体干扰和传感器中毒的问题。设计了一种新型气室,增强了气体对光的吸收,并有效降低了环境温度、灰尘、震动等因素对检测的影响。由于使用LED作为光源,降低了使用中的成本,使该系统的实际应用成为可能。实验结果表明：该系统的测量灵敏度可达10×10^-6,误差始终控制在2％以内,具有很高的稳定性。     

A multi-temporal method for cloud detection, applied to FORMOSAT-2, VENµS, LANDSAT and SENTINEL-2 images

Over lands, the cloud detection on remote sensing images is not an easy task, because of the frequent difficulty to distinguish clouds from the underlying landscape, even at a high resolution. Up to now, most high resolution images have been distributed without an associated cloud mask. This situation should change in the near future, thanks to two new satellite missions that will provide optical images combining 3 features: high spatial resolution, high revisit frequency and constant viewing angles. The VENµS (French and Israeli cooperation) mission should be launched in 2012 and the European SENTINEL-2 mission in 2013. Fortunately, two existing satellite missions, FORMOSAT-2 and LANDSAT, enable to simulate the future data of these sensors.Multi-temporal imagery at constant viewing angles provides a new way to discriminate clouded and unclouded pixels, using the relative stability of the earth surface reflectances compared to the quick variations of the reflectance of pixels affected by clouds. In this study, we have used time series of images from FORMOSAT-2 and LANDSAT to develop and test a Multi-Temporal Cloud Detection (MTCD) method. This algorithm combines a detection of a sudden increase of reflectance in the blue wavelength on a pixel by pixel basis, and a test of the linear correlation of pixel neighborhoods taken from couples of images acquired successively.MTCD cloud masks are compared with cloud cover assessments obtained from FORMOSAT-2 and LANDSAT data catalogs. The results show that the MTCD method provides a better discrimination of clouded and unclouded pixels than the usual methods based on thresholds applied to reflectances or reflectance ratios. This method will be used within VENµS level 2 processing and will be proposed for SENTINEL-2 level 2 processing.     

基于功能化核酸和金属离子的荧光传感

荧光传感器能够将微观的分子识别事件转换成宏观可测的荧光信号,荧光法在灵敏度、选择性和实时原位检测等方面优势突出.该文主要介绍以功能化核酸和金属离子相互作用为基础而设计的荧光传感器的研究进展.     

灰色预测和混沌PSO的红外小目标检测

在分析红外图像弱小目标和背景特征的基础上,提出了一种基于灰色预测和混沌PSO的红外小目标检测方法.该方法首先采用灰色系统理论中的GM(1.1)模型对红外图像中的背景进行时域预测,并用实际图像减去预测图像得到残差图像,在抑制背景的同时增强了目标;然后提出了混沌粒子群优化(particle swarm optimizati...     

基于回归系数的变量筛选方法用于近红外光谱分析

提出了一种基于回归系数的变量逐步筛选方法。对光谱中各变量计算其回归系数后,按其绝对值由大到小将相应变量排列,采用PLS交互检验按前向选择法逐步选择最佳变量子集。用该方法对玉米和柴油近红外光谱数据进行分析,对玉米蛋白质、柴油十六烷值和粘度分别选择出了14、12以及30个最佳变量用于建模,所得预测结果均优于全谱变量建模的预测结果。可见本方法是一种有效实用的近红外光谱变量选择方法。     

硝基芳烃类炸药检测用荧光传感器研究进展

微痕量炸药的准确、快速检测对反恐、非金属地雷探测、环境质量监测等都具有十分重要的意义。在概括现有炸药检测技术的基础上,着重介绍用于微痕量硝基芳烃类炸药检测的均相荧光传感器、薄膜荧光传感器和光纤荧光传感器,其中,薄膜荧光传感器因其灵敏度高、选择性好、可重复使用和易于器件化等优点将在微痕量硝基芳烃类炸药的检测中获得实际应用。     

A highly selective triphenylamine-based indolylmethane derivatives as colorimetric and turn-off fluorimetric sensor toward Cu detection by deprotonation of secondary amines

A new triphenylamine-based fluorogenic probe bearing an indolylmethane unit (R1) was developed as a fluorescent chemosensor with high selectivity toward Cu²⁺ over other cations tested. The new probe R1 only sensed Cu²⁺ among heavy and transition metal (HTM) ions in CH₃CN/H₂O (70/30, v/v) solution. The capture of Cu²⁺ by the receptor resulted in deprotonation of the secondary amine conjugated to the triphenylamine, so that the electron-donation ability of the “N” atom would be greatly enhanced; thus sensor showed a 250 nm change in the new absorption band (from 291 nm to 541 nm) and a large colorimetric response, it also exhibited the large decrease in fluorescence intensity at 378 nm and affinity to Cu²⁺ over other cations such as Hg²⁺, Fe³⁺, Pb²⁺, Zn²⁺, Cd²⁺, Ni²⁺, Co²⁺ and Mn²⁺ make this compound a useful chemosensor for Cu²⁺ detection in CH₃CN/H₂O (70/30, v/v) mixture. The probe R1 (c = 1.0 × 10⁻⁶ M) displayed significant fluorescence change and colorimetric change upon addition of Cu²⁺ among the metal ions examined.     

基于独立成分的局部建模方法及其在近红外光谱分析中的应用研究

建立了一种基于独立成分分析的局部建模新方法,该方法首先将独立成分分析(ICA)用于近红外光谱的特征提取,然后,根据所提取的独立成分选择校正集中与预测样本相邻近的样本构成校正子集,建立局部偏最小二乘(PLS)回归模型并对预测样本进行预测。将所提出的方法应用于烟草样品中尼古丁含量的测定,所得结果优于常用的全局建模方法。     

Particle swarm optimization based fusion of near infrared and visible images for improved face verification

This paper presents two novel image fusion schemes for combining visible and near infrared face images (NIR), aiming at improving the verification performance. Sub-band decomposition is first performed on the visible and NIR images separately. In both cases, we further employ particle swarm optimization (PSO) to find an optimal strategy for performing fusion of the visible and NIR sub-band coefficients. In the first scheme, PSO is used to calculate the optimum weights of a weighted linear combination of the coefficients. In the second scheme, PSO is used to select an optimal subset of features from visible and near infrared face images. To evaluate and compare the efficacy of the proposed schemes, we have performed extensive verification experiments on the IRVI database. This database was acquired in our laboratory using a new sensor that is capable of acquiring visible and near infrared face images simultaneously thereby avoiding the need for image calibration. The experiments show the strong superiority of our first scheme compared to NIR and score fusion performance, which already showed a good stability to illumination variations.     

靶场红外测量图像弱信号小目标检测系统的设计与实现

分析了红外图像中小目标、噪声以及背景的特点,考虑到单帧图像处理不能兼顾对目标的可靠检测和低的虚警概率,而现有的多帧检测算法计算量大,难以实时实现,采用了将单帧和多帧检测有机结合的小目标检测技术.首先采用基于高阶统计量的目标检测算法,从单帧强噪声图像中检测出虚警率低的候选目标点;然后针对小目标运动的一致性和连续性,采用多帧高阶互相关的序列图像处理方法,得到目标运动轨迹;最后再对目标运动轨迹进行综合评判,进行航迹确认,得到真实目标的位置和轨迹.实验结果表明,该技术降低了虚警概率,提高了检测概率.     

A colorimetric and ratiometric fluorescent probe for quantitative detection of GSH at physiologically relevant levels

A naphthalene derivate containing piazselenole (NDP) has been developed as an example of colorimetric and ratiometric fluorescent probes for glutathione (GSH) at physiologically relevant concentration. Upon addition of GSH, the probe displayed a ratiometric fluorescent response with an enhancement of the ratios of emission intensities at 436 and 615 nm, accompanied with the solution color change from jacinth to colorlessness. The detection range is 0-80 mM with the detection limit of 0.178 mM. Moreover, the probe showed good selectivity and satisfying results in the determination of GSH. As the linear response range covers the concentration range of biological samples, the probe may have the potential to determine GSH directly in biological samples in the future.     

PET瓶封盖质量在线检测系统的设计与实现

设计了一套完整的基于DSP+ARM双核处理器的PET瓶封盖质量检测系统。首先通过DSP DM642完成对图像传感器MT9P031的RAW原始数据采集,然后对采集的PET瓶图像进行定位并实现相关的图像处理算法,最后采用ARM11嵌入式系统对整个传动设备进行监控。经过实际生产线的应用证明,该在线检测系统能够胜任在高速PET瓶封盖生产线中的应用。